simdat

A dataset containing the sine wave data with random noise added.

datasets

GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999)
as implemented in the R package 'mgcv' (Wood, S.N., 2006; 2011) is a nonlinear
regression analysis which is particularly useful for time course data such as
EEG, pupil dilation, gaze data (eye tracking), and articulography recordings,
but also for behavioral data such as reaction times and response data. As time
course measures are sensitive to autocorrelation problems, GAMMs implements
methods to reduce the autocorrelation problems. This package includes functions
for the evaluation of GAMM models (e.g., model comparisons, determining regions
of significance, inspection of autocorrelational structure in residuals)
and interpreting of GAMMs (e.g., visualization of complex interactions, and
contrasts).

Jacolien van Rij

itsadug

Interpreting Time Series and Autocorrelated Data Using GAMMs

Martijn Wieling

R. Harald Baayen

Hedderik van Rijn

simdat function

A data frame with 75600 rows and 6 variables:<dl class="dl-horizontal">
 <dt><code>Group</code></dt><dd>Age group of participants: Adults or Children.</dd>
 <dt><code>Time</code></dt><dd>Time, time measure from start of each time series.</dd>
 <dt><code>Trial</code></dt><dd>Trial in the experiment, centered around zero.</dd>
 <dt><code>Condition</code></dt><dd>Continuous variable, ranging from -1 to 4. 
For example, stimulus onset asynchrony.</dd>
 <dt><code>Subject</code></dt><dd>Code for individual participants.</dd>
 <dt><code>Y</code></dt><dd>Time series measure. 
Similar to pupil size, sensor position, or voltage.</dd>
</dl>

Format

Simulated time series data. — simdat

A data frame with 75600 rows and 6 variables:<dl class='dl-horizontal'>
 <dt><code>Group</code></dt><dd>Age group of participants: Adults or Children.</dd>
 <dt><code>Time</code></dt><dd>Time, time measure from start of each time series.</dd>
 <dt><code>Trial</code></dt><dd>Trial in the experiment, centered around zero.</dd>
 <dt><code>Condition</code></dt><dd>Continuous variable, ranging from -1 to 4. 
For example, stimulus onset asynchrony.</dd>
 <dt><code>Subject</code></dt><dd>Code for individual participants.</dd>
 <dt><code>Y</code></dt><dd>Time series measure. 
Similar to pupil size, sensor position, or voltage.</dd>
</dl>

simdat: Simulated time series data.

Description

Usage

Arguments

Format